Images that contain one or more objects may be viewed, developed, and modified using a software application. Objects may be any object represented in the image using pixels of one or more colors. Examples of objects include humans, non-human animals, trees, buildings, and products. Images can be obtained via a digital camera or otherwise, and provided to a software application. The software application can be used to view the image and modify the image. For example, object effects, such as additional shapes or colors, or object shape warping can be applied using the software application. The user may access a tool included with the software application to apply object effects.
Some images contain defective image coloring that may be the result of too little or too much lighting or reflections of light by the object. One example of such defects may be red-eye effect in photographs of human or animal eyes. Red-eye effect can occur when light from a camera flash occurs before an eye pupil closes or becomes smaller. The light is reflected by the retina at the back of the eye. The retina is a blood rich area and reflections can result in a red appearance in the eye. Red-eye effect in non-human animal photographs may be even more pronounced. Many animals include a light-reflecting layer, called the tapetum, behind the retina that improves night vision. Such a layer magnifies red-eye effect and can result in different colors for eyes, such as red, blue, yellow, pink, or green, in animal photographs.
Some computer applications provide tools that can be used to minimize or remove the image defects such as red-eye effects. Conventional computer applications utilize a heuristic process to correct red-eye effects. The heuristic process includes desaturating each pixel associated with the red-eye affected area to a shade of gray and replacing the pixels with a pixels having a more natural color. Such a process can be effective in minimizing or eliminating red-eye effects in some images.
The heuristic process may be ineffective in some image object configurations. For example, when the object is far from the camera or the image was obtained in an environment having low light levels, object eyes may appear as an amber colored glow and the heuristic process tool may be unable to clearly define the boundaries of the red-eye effect area. Other situations in which the heuristic process may be ineffective include when (1) the object is not facing in the direction of the camera; (2) non-human animal eyes that contain bright red-eye effects; and (3) users have difficulty selecting a more natural eye color.
Other examples of defective image coloring include faded or discolored teeth or other facial or body features for human and non-human objects. A heuristic process similar to that used to correct red-eye effects may be applied to such features, but deficiencies such as those noted above may be experienced. Accordingly, a need exists for a tool that can be used to minimize or eliminate image defects in a greater variety of image object situations.